Isolating error-based and reward-based learning in a real-world task via gradual perturbations in embodied VR
File(s)
Accepted version
Author(s)
Nardi, Federico
Arora, Aaruni
Faisal, Aldo
Haar, Shlomi
Type
Journal Article
Abstract
Error-based and reward-based mechanisms act together in real-world motor learning. Lab tasks separate them by manipulating feedback, but we previously showed that in a real world task the correction of a large error is rewarding in itself, and engages reward-based learning even without a reward signal. Here we asked whether they separate when errors are kept small. We used embodied virtual reality of pool billiards, in which the visual scene
is aligned with a physical table, and rotated the cue ball’s seen trajectory gradually while haptics and proprioception stayed unchanged. Thirty-two participants played two sessions, learning the same rotation with error-only feedback in one and reward-only feedback in the
other. Their exploration after failed shots, and their post-movement beta rebound over the motor cortex, differed between sessions. Gradual perturbations can therefore isolate the two mechanisms in a real-world task, and open a way to target them in rehabilitation and skill training.
is aligned with a physical table, and rotated the cue ball’s seen trajectory gradually while haptics and proprioception stayed unchanged. Thirty-two participants played two sessions, learning the same rotation with error-only feedback in one and reward-only feedback in the
other. Their exploration after failed shots, and their post-movement beta rebound over the motor cortex, differed between sessions. Gradual perturbations can therefore isolate the two mechanisms in a real-world task, and open a way to target them in rehabilitation and skill training.
Date Acceptance
2026-08-28
Citation
iScience
ISSN
2589-0042
Publisher
Elsevier
Journal / Book Title
iScience
Copyright Statement
Copyright This paper is embargoed until publication. Once published the Version of Record (VoR) will be available on immediate open access.
License URL
Publication Status
Accepted